5 citations · 8 across the 4 of their papers we have counts for
4 papers
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
Chenjie Cao, Xinlin Ren, Yanwei Fu
Recent advancements in learning-based Multi-View Stereo (MVS) methods have prominently featured transformer-based models with attention mechanisms. However, existing approaches hav…
Local Consensus Enhanced Siamese Network with Reciprocal Loss for Two-view Correspondence Learning
Linbo Wang, Jing Wu, Xianyong Fang +3
Recent studies of two-view correspondence learning usually establish an end-to-end network to jointly predict correspondence reliability and relative pose. We improve such a framew…
Rethinking Optical Flow from Geometric Matching Consistent Perspective
Qiaole Dong, Chenjie Cao, Yanwei Fu
Optical flow estimation is a challenging problem remaining unsolved. Recent deep learning based optical flow models have achieved considerable success. However, these models often…
Rethinking the Multi-view Stereo from the Perspective of Rendering-based Augmentation
Chenjie Cao, Xinlin Ren, Xiangyang Xue +1
GigaMVS presents several challenges to existing Multi-View Stereo (MVS) algorithms for its large scale, complex occlusions, and gigapixel images. To address these problems, we firs…